Digital image processing has become a significant form of image processing because of continuing improvements in techniques and increasingly powerful hardware devices. Digital image processing techniques have augmented and, in some cases, replaced methods used by photographers in image composition and dark room processing. For example, digital image processing techniques such as contrast balancing, edge sharpening, color balancing or retouching of defects are employed for editing original photographic images. Moreover, with the aid of a computer, digitized images can be edited to achieve a variety of effects such as changing the shapes and colors of objects and forming composite images.
Until recently, real-time editing of digital graphic images was feasible only on expensive high-performance workstations with dedicated, special-purpose, hardware. The progress of integrated circuit technology in recent years has produced microprocessors with significantly improved processing power and has also reduced the costs of computer memories. These developments have made it feasible to implement advanced graphic editing techniques in personal computers. These editing techniques, however, are typically complex and require a technical and/or artistic expertise beyond that of ordinary users of personal computers.
For example, image compositing is a digital image processing technique that merges unrelated objects from multiple images. The result is a new scene that may never have existed physically. Image compositing has gained widespread use in photography. Image compositing operations, however, typically require a complex procedure for compositing the various images in order to achieve the desired effect. Thus, although the standard PC of today is capable of implementing these complex procedures, the average user is not.
Another common digital image processing technique is geometric transformations, which reposition pixels within an image. Using a mathematical transformation, pixels are relocated from their (x,y) spatial coordinates in the input image to a new coordinate in the output image. Geometric transformations are used to change the color of an object or to move, spin, size and arbitrarily contort its geometry. In digital photography these transformations are typically used to implement touch-up techniques such as correcting distortions in an image, as well as adding visual effects. Like image compositing, geometric transformations can be done on a PC platform. However, employing these transformations requires an expertise that is beyond that of the average user.
Well known computer vision and pattern recognition techniques involves automatic registering of a model with an image. Also, head models have been proposed for low-bandwidth video communication. For example, someone's head is mapped to a 3D-head model and then only the parameters of the model are sent. Similar head models have also been used in proposed face recognition systems. These type of model registration techniques, however, are unavailable for imaging processing and editing.
There is a need for a digital imaging processing system in which techniques such as those described above and others can be applied to an image without requiring either technical or artistic skills. Such a system would allow a user to directly edit images without requiring the aid of a specialist.